Incremental-DETR: Incremental Few-Shot Object Detection via Self-Supervised Learning. (arXiv:2205.04042v2 [cs.CV] UPDATED)

Incremental few-shot object detection aims at detecting novel classes without
forgetting knowledge of the base classes with only a few labeled training data
from the novel classes. Most related prior works are on incremental object
detection that rely on the availability of abundant training samples per novel
class that substantially limits the scalability to real-world setting where
novel data can be scarce. In this paper, we propose the Incremental-DETR that
does incremental few-shot object detection via fine-tuning and self-supervised
learning …

arxiv cv detection incremental learning self-supervised learning supervised learning